Target Trajectory Tracking Control of Quadrotor UAV Based on Recurrent Neural Network
A reliable target trajectory tracking controller is designed to address the issues of external wind disturbances and model uncertainties encountered during fllight of quadrotor unmanned aerial vehicle(UAV)within natural environments.An adaptive sliding mode control method based on recurrent neural network(RNN)is proposed.Regarding starting from the dynamics model of quadrotor UAV,the fully ac-tuated and underactuated subsystems are considered separately.By combining external wind disturbances with model uncertainties and then integrating into total disturbance terms,a recurrent neural network is used to estimate the total disturbance terms adaptively.Based on Lyapunov theory,a feedback compensation adaptive sliding mode controller is designed.Thus,the effectiveness of the proposed control method is fully verified through theoretical and comparative simulations.
Quadrotor UAVRecurrent neural networkAdaptive sliding mode controlTracking control
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